Improving the Accuracy of Ballot Scanners Using Supervised Learning

Author:

Barretto Sameer,Chown William,Meyer David,Soni Aditya,Tata Atreya,Halderman J. Alex

Publisher

Springer International Publishing

Reference31 articles.

1. Bajcsy, A., Li-Baboud, Y.-S., Brady, M.: Systematic measurement of marginal mark types on voting ballots. Technical report (2015). https://nvlpubs.nist.gov/nistpubs/ir/2015/NIST.IR.8069.pdf. NIST

2. Bowen, D.: Top-to-Bottom Review of voting machines certified for use in California. Technical report (2007). https://www.sos.ca.gov/elections/voting-systems/oversight/top-bottom-review/. California Secretary of State

3. Bradski, G.: The OpenCV library. Dr. Dobb’s J. Softw. Tools (2000)

4. Clark, A.: Pillow (PIL Fork) Documentation (2015). https://buildmedia.readthedocs.org/media/pdf/pillow/latest/pillow.pdf

5. Colorado Secretary of State Elections Division: Voter Intent: Determination of Voter Intent for Colorado Elections (2013). https://www.broomfield.org/DocumentCenter/View/11702/Voter-Intent-Guide

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1. Ballot Tabulation Using Deep Learning;2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI);2023-08

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